Developing indices of abundance using habitat data in a statistical framework

We describe the statistical application of the habitat-based standardization (statHBS) of catch-per-unit-effort (CPUE) data to derive indices of relative abundance. The framework is flexible, including multiple component models to accommodate factors such as habitat, sampling, and animal behavior. It allows the use of prior information or the completely independent estimation of model components (e.g., habitat preference). The integration with a general linear model framework allows convenient comparison with traditional methods used to standardize CPUE data. The statistical framework allows model selection and estimation of uncertainty. The statHBS model is applied to bigeye tuna in the western and central Pacific Ocean. We describe several additional improvements to the methodology.